This repository includes the code and notebooks for generating the data and running the experiments reported in
Zinemanas P., Cancela P., Rocamora M. "End–to–end Convolutional Neural Networks for Sound Event Detection in Urban Environments" in Proceedings of the 24th Conference of Open Innovations Association FRUCT, 3rd IEEE FRUCT International Workshop on Semantic Audio and the Internet of Things, Moscow, Russia. ISSN 2305-7254, ISBN 978-952-68653-8-6, FRUCT Oy, e-ISSN 2343-0737 (license CC BY-ND), pages 533-539, 8-12 April 2019.
The repository has the following folders:
sed_endtoend --> Main source files for data generation, network models and callbacks.
exps --> Jupyter notebooks to run the experiments.
utils --> Some useful scripts to work with the dataset.